Multicast Scaling in Heterogeneous Wireless Sensor Networks for Security and Time Efficiency Ramdas Vankdothu, Mohd Abdul Hameed, Husnah Fatima, Akkala Subbarao Wireless Personal Communications, 2025 Heterogeneous wireless sensor networks (HWSNs) satisfy researchers' requirements for developing real-world solutions that handle unattended challenges. However, the primary constraint of researchers is the privacy of the sensor nodes. It safeguards the sensor nodes and extensions in the HWSNs. Therefore, it is necessary to develop secure operational systems. Multicast scaling with security and time efficiency is described in heterogeneous wireless sensor networks to maximize network performance while also successfully protecting network privacy. This study evaluates the initial security and time efficiency measures, such as execution time, transmission delay, processing delay, congestion level, and trust measure. Subsequently, the optimal location of the heterogeneous nodes is determined using sigmoid-based fuzzy c-means clustering. Finally, successful cluster routing was achieved via support-value-based particle swarm optimization. The experimental results indicate that the proposed strategy surpasses existing strategies in terms of network delivery ratio, end-to-end delay, throughput, packet delivery, and node remaining energy level.
An Effective Congestion and Interference Secure Routing Protocol for Internet of Things Applications in Wireless Sensor Network Ramdas Vankdothu, Mohd Abdul Hameed Wireless Personal Communications, 2025 This paper provides an effective Wireless Sensor Network (WSN) routing solution for Internet of Things (IoT) applications cognizant of congestion, security, and interference. Because several sources try to deliver their packets to a destination simultaneously, which is a common case in IoT applications. The proposed congestion and interference aware safe routing protocol is claimed to work in networks with high traffic. The signal to interference ratio (SINR), congestion level, and survival factor is used in our suggested procedure to estimate the cluster head selection factor first. The adaptive fuzzy c-means clustering method clusters the network nodes based on the cluster head selection factor. After that, data packets are encrypted using Adaptive Quantum Logic-based packet coding. Finally, the Adaptive Krill Herd (AKH) optimization method identifies the least congested corridor, resulting in optimal data transmission routing. The exploratory findings show that the provided strategy outperforms previous methodologies in network performance, end-to-end delay, packet delivery ratio, and node remaining energy level.
Machine Learning on Geospatial Data Ayesha Ameen, Tanveer Sultana, Ayesha Banu, Syed Mohd Ali, Mohd Abdul Hameed 2025 IEEE International Conference on Next Gen Technologies of Artificial Intelligence and Geoscience Remote Sensing Earthsense 2025, 2025
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Multicast scaling in heterogeneous wireless sensor networks for security and time efficiency R Vankdothu, MA Hameed, H Fatima, A Subbarao Wireless Personal Communications, 1-17 , 2025 2025 Citations: 3
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Correction to: An Effective Congestion and Interference Secure Routing Protocol for Internet of Things Applications in Wireless Sensor Network R Vankdothu, MA Hameed Wireless Personal Communications 140 (1), 163-163 , 2025 2025
RETRACTED ARTICLE: An Effective Congestion and Interference Secure Routing Protocol for Internet of Things Applications in Wireless Sensor Network R Vankdothu, MA Hameed Wireless Personal Communications 140 (1), 143-161 , 2025 2025 Citations: 16
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